code: def _get_grid_tv_loss(
      grid, log_domain: bool = True, eps: float = 1e-5
  ):
      if log_domain:
          if (grid <= -eps).any():
              warnings.warn(
                  "Grid has negative values; this will produce NaN loss"
              )
          grid = torch.log(grid + eps)
  
      # this is an isotropic version, note that it ignores last rows/cols
      return torch.mean(
          utils.safe_sqrt(
              (grid[..., :-1, :-1, 1:] - grid[..., :-1, :-1, :-1]) ** 2
              + (grid[..., :-1, 1:, :-1] - grid[..., :-1, :-1, :-1])
              ** 2
              + (grid[..., 1:, :-1, :-1] - grid[..., :-1, :-1, :-1])
              ** 2,
              eps=1e-5,
          )
      )
  
imports: import warnings
  from typing import Any, Dict, Optional
  import torch
  from pytorch3d.implicitron.models.renderer.ray_sampler import ImplicitronRayBundle
  from pytorch3d.implicitron.tools import metric_utils
  from pytorch3d.implicitron.tools.config import registry, ReplaceableBase
  from pytorch3d.ops import padded_to_packed
  from pytorch3d.renderer import utils
  from .renderer.base import RendererOutput
label_desc: Use image node_id 3 for calling a global function with example usage: _get_grid_tv_loss(grid, log_domain, eps) and returns: torch